File size: 3,225 Bytes
b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d b4c6da9 ce1bc2d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 |
---
library_name: peft
license: other
base_model: SeaLLMs/SeaLLM3-7B-Chat
tags:
- axolotl
- generated_from_trainer
model-index:
- name: proof-reading-SeaLLM3-7B-Chat-3090-v11
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.5.0`
```yaml
base_model: SeaLLMs/SeaLLM3-7B-Chat
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: Tippawan/p11-seallm
type: chat_template
conversation: chatml
field_messages: messages
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.00 #editted 2
output_dir: ./outputs/outputs_name
sequence_len: 2048
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: false
push_to_hub: true
hub_model_id: Tippawan/proof-reading-SeaLLM3-7B-Chat-3090-v11 # Replace with your Hugging Face repo ID
use_auth_token: true # Ensure you have set your Hugging Face API token in the environment
hub_private_repo: true # Set to true if you want the repository to be private
hub_strategy: all_checkpoints
save_total_limit: 3
load_best_model_at_end: true
adapter: lora
lora_model_dir: Tippawan/proof-reading-SeaLLM3-7B-Chat-3090-v9
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project: proof-reading-SeaLLM3-7B-Chat-3090-v11
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1 #editted 3
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
seed: 42
warmup_steps: 10
evals_per_epoch: 1
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
```
</details><br>
# proof-reading-SeaLLM3-7B-Chat-3090-v11
This model is a fine-tuned version of [SeaLLMs/SeaLLM3-7B-Chat](https://huggingface.co/SeaLLMs/SeaLLM3-7B-Chat) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.1
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3 |